Development and Validation of SCACOMS, a Composite Scale for Assessing Disease Progression and Treatment Effects in Spinocerebellar Ataxia.

Spinocerebellar ataxias (SCA) are rare inherited neurodegenerative disorders characterized by a progressive impairment of gait, balance, limb coordination, and speech. There is currently no composite scale that includes multiple aspects of the SCA experience to assess disease progression and treatment effects. Applying the method of partial least squares (PLS) regression, we developed the Spinocerebellar Ataxia Composite Scale (SCACOMS) from two SCA natural history datasets (NCT01060371, NCT02440763). PLS regression selected items based on their ability to detect clinical decline, with optimized weights based on the item's degree of progression. Following model validation, SCACOMS was leveraged to examine disease progression and treatment effects in a 48-week SCA clinical trial cohort (NCT03701399). Items from the Clinical Global Impression-Global Improvement Scale (CGI-I), the Friedreich Ataxia Rating Scale (FARS) - functional stage, and the Modified Functional Scale for the Assessment and Rating of Ataxia (f-SARA) were objectively selected with weightings based on their sensitivity to clinical decline. The resulting SCACOMS exhibited improved sensitivity to disease progression and greater treatment effects (compared to the original scales from which they were derived) in a 48-week clinical trial of a novel therapeutic agent. The trial analyses also provided a SCACOMS-derived estimate of the temporal delay in SCA disease progression. SCACOMS is a useful composite measure, effectively capturing disease progression and highlighting treatment effects in patients with SCA. SCACOMS will be a powerful tool in future studies given its sensitivity to clinical decline and ability to detect a meaningful clinical impact of disease-modifying treatments.

The Detection of Environmental Influences on Academic Achievement Appears to Depend on the Analytic Approach.

One long-standing analytic approach in adoption studies is to examine correlations between features of adoptive homes and outcomes of adopted children (hereafter termed 'measured environment correlations') to illuminate environmental influences on those associations. Although results from such studies have almost uniformly suggested modest environmental influences on adopted children's academic achievement, other work has indicated that adopted children's achievement is routinely higher than that of their reared-apart family members, often substantially so. We sought to understand this discrepancy. We examined academic achievement and literacy-promotive features of the home in 424 yoked adoptive/biological families participating in the Early Growth and Development Study (EGDS; i.e., adopted children, adoptive mothers, birth mothers, and biological siblings of the adopted children remaining in the birth homes) using an exhaustive modeling approach. Results indicated that, as anticipated, adopted children scored up to a full standard deviation higher on standardized achievement tests relative to their birth mothers and reared-apart biological siblings. Moreover, these achievement differences were associated with differences in the literacy-promotive features of the adoptive and birth family homes, despite minimal measured environment correlations within adoptive families. A subsequent simulation study highlighted noise in measured environmental variables as an explanation for the decreased utility of measured environment correlations. We conclude that the field's heavy focus on measured environment correlations within adoptive families may have obscured detection of specific environmental effects on youth outcomes, and that future adoption studies should supplement their measured environment analyses with mean differences between reared-apart relatives.

A novel approach to model cumulative stress: Area under the s-factor curve.

OBJECTIVE: Using a large longitudinal sample of adults from the Midlife in the United States (MIDUS) study, the present study extended a recently developed hierarchical model to determine how best to model the accumulation of stressors, and to determine whether the rate of change in stressors or traditional composite scores of stressors are stronger predictors of health outcomes. METHOD: We used factor analysis to estimate a stress-factor score and then, to operationalize the accumulation of stressors we examined five approaches to aggregating information about repeated exposures to multiple stressors. The predictive validity of these approaches was then assessed in relation to different health outcomes. RESULTS: The prediction of chronic conditions, body mass index, difficulty with activities of daily living, executive function, and episodic memory later in life was strongest when the accumulation of stressors was modeled using total area under the curve (AUC) of estimated factor scores, compared to composite scores that have traditionally been used in studies of cumulative stress, as well as linear rates of change. CONCLUSIONS: Like endogenous, biological markers of stress reactivity, AUC for individual trajectories of self-reported stressors shows promise as a data reduction technique to model the accumulation of stressors in longitudinal studies. Overall, our results indicate that considering different quantitative models is critical to understanding the sequelae and predictive power of psychosocial stressors from midlife to late adulthood.

An integrative approach for the analysis of risk and health across the life course: challenges, innovations, and opportunities for life course research.

Life course epidemiology seeks to understand the intricate relationships between risk factors and health outcomes across different stages of life to inform prevention and intervention strategies to optimize health throughout the lifespan. However, extant evidence has predominantly been based on separate analyses of data from individual birth cohorts or panel studies, which may not be sufficient to unravel the complex interplay of risk and health across different contexts. We highlight the importance of a multi-study perspective that enables researchers to: (a) Compare and contrast findings from different contexts and populations, which can help identify generalizable patterns and context-specific factors; (b) Examine the robustness of associations and the potential for effect modification by factors such as age, sex, and socioeconomic status; and (c) Improve statistical power and precision by pooling data from multiple studies, thereby allowing for the investigation of rare exposures and outcomes. This integrative framework combines the advantages of multi-study data with a life course perspective to guide research in understanding life course risk and resilience on adult health outcomes by: (a) Encouraging the use of harmonized measures across studies to facilitate comparisons and synthesis of findings; (b) Promoting the adoption of advanced analytical techniques that can accommodate the complexities of multi-study, longitudinal data; and (c) Fostering collaboration between researchers, data repositories, and funding agencies to support the integration of longitudinal data from diverse sources. An integrative approach can help inform the development of individualized risk scores and personalized interventions to promote health and well-being at various life stages.

Cohort Changes and Sex Differences After Age 50 in Cognitive Variables in the English Longitudinal Study of Ageing.

OBJECTIVES: This paper models cognitive aging, across mid and late life, and estimates birth cohort and sex differences in both initial levels and aging trajectories over time in a sample with multiple cohorts and a wide span of ages. METHODS: The data used in this study came from the first 9 waves of the English Longitudinal Study of Ageing, spanning 2002-2019. There were n = 76,014 observations (proportion male 45%). Dependent measures were verbal fluency, immediate recall, delayed recall, and orientation. Data were modeled using a Bayesian logistic growth curve model. RESULTS: Cognitive aging was substantial in 3 of the 4 variables examined. For verbal fluency and immediate recall, males and females could expect to lose about 30% of their initial ability between the ages of 52 and 89. Delayed recall showed a steeper decline, with males losing 40% and females losing 50% of their delayed recall ability between ages 52 and 89 (although females had a higher initial level of delayed recall). Orientation alone was not particularly affected by aging, with less than a 10% change for either males or females. Furthermore, we found cohort effects for initial ability level, with particularly steep increases for cohorts born between approximately 1930 and 1950. DISCUSSION: These cohort effects generally favored later-born cohorts. Implications and future directions are discussed.

It Runs in the Family: Testing for Longitudinal Family Flynn Effects.

The Flynn effect refers to increases over time in measured (particularly fluid) intelligence of approximately 3 IQ points per decade. We define the Flynn effect at the family level, using longitudinal data and two new family-level cohort definitions. Multilevel growth curve analyses of the National Longitudinal Survey of Youth 1979 data showed that children in families with later-born mothers had higher average PIAT math scores, and lower average reading comprehension scores and growth, in young and middle childhood. Children in families where the first child was born later had higher average PIAT math, reading recognition, and reading comprehension scores, as well as larger developmental growth. The latter family-level Flynn effects were of higher magnitudes than the usual individual-level Flynn effect found in previous studies. Our results, showing family level-intercept and slope Flynn effects for both maternal birthyear and first child birthyear, have implications for research aiming to explain the Flynn effect.

Getting a Grip on Secular Changes: Age-Period-Cohort Modeling of Grip Strength in the English Longitudinal Study of Ageing.

BACKGROUND: Grip strength is a popular and valuable measure in studies of physical functional capabilities in old age. The influence of historical trends and differential period-specific exposures can complicate the interpretation of biomarkers of aging and health and requires careful analysis and interpretation of aging, birth cohort, and period effects. This study evaluates the effects of aging, period, and cohort on grip strength in a population of adults and older adults. METHODS: We use more than 27 000 observations for individuals at least 50 years of age, born in approximately 1910-1960, from the English Longitudinal Study of Ageing to examine a variety of multilevel and cross-classified modeling approaches to evaluate age, period, and cohort effects. Our results extended Hierarchical Age-Period-Cohort modeling and compared our results with a set of 9 submodels with explicit assumptions to determine the most reliable modeling approach. RESULTS: Findings suggest grip strength is primarily related to age, with minimal evidence of either period and/or cohort effects. Each year's increase in a person's age was associated with a 0.40-kg decrease in grip strength, though this decline differs by gender. CONCLUSIONS: We conclude that as the population ages, grip strength declines at a systematic and predictable rate equal to -0.40 kg per year (approximately -0.50 kg for men and -0.30 kg for women) in residents of England aged 50 and older. Age effects were predominant and most consistent across methodologies. While there was some evidence for cohort effects, such effects were minimal and therefore indicative that grip strength is a consistent physiological biomarker of aging.

Home Improvement: Evaluating Secular Changes in NLSY HOME-Cognitive Stimulation and Emotional Support Scores.

This study evaluated changes over time in the quality of children's home environment, using the Home Observation Measurement of the Environment (HOME). Longitudinal increases in HOME scores were predicted by both theory and past empirical results. Analysis of the National Longitudinal Survey of Youth Children data (N = 5715, aged 0-14) suggested that HOME scores have been increasing, and that the increase is a family-level phenomenon. The data were a sample of children born to mothers who were approximately representative of the United States in 1979. An increase in HOME scores occurred primarily for the three age categories younger than ten. Effect sizes were of approximately the same magnitude as the Flynn effect for intelligence. These results have implications for policy and future research regarding the home environment.

Cohort and Period Effects as Explanations for Declining Dementia Trends and Cognitive Aging.

Studies have reported that the age-adjusted incidence of cognitive impairment and dementia may have decreased over the past two decades. Aging is the predominant risk factor for Alzheimer's disease and related dementias and for neurocognitive decline. However, aging cannot explain changes in overall age-adjusted incidence of dementia. The objective of this position paper was to describe the potential for cohort and period effects in cognitive decline and incidence of dementia. Cohort effects have long been reported in demographic literature, but starting in the early 1980s, researchers began reporting cohort trends in cognitive function. At the same time, period effects have emerged in economic factors and stressors in early and midlife that may result in reduced cognitive dysfunction. Recognizing that aging individuals today were once children and adolescents, and that research has clearly noted that childhood cognitive performance is a primary determinant of old-age cognitive performance, this is the first study that proposes the need to connect known cohort effects in childhood cognition with differences in late-life functioning.

A Simulation Study of Bootstrap Approaches to Estimate Confidence Intervals in DeFries-Fulker Regression Models (with Application to the Heritability of BMI Changes in the NLSY).

The univariate bootstrap is a relatively recently developed version of the bootstrap (Lee and Rodgers in Psychol Methods 3(1): 91, 1998). DeFries-Fulker (DF) analysis is a regression model used to estimate parameters in behavioral genetic models (DeFries and Fulker in Behav Genet 15(5): 467-473, 1985). It is appealing for its simplicity; however, it violates certain regression assumptions such as homogeneity of variance and independence of errors that make calculation of standard errors and confidence intervals problematic. Methods have been developed to account for these issues (Kohler and Rodgers in Behav Genet 31(2): 179-191, 2001), however the univariate bootstrap represents a unique means of doing so that is presaged by suggestions from previous DF research (e.g., Cherny et al. in Behav Genet 22(2): 153-162, 1992). In the present study we use simulations to examine the performance of the univariate bootstrap in the context of DF analysis. We compare a number of possible bootstrap schemes as well as more traditional confidence interval methods. We follow up with an empirical demonstration, applying results of the simulation to models estimated to investigate changes in body mass index in adults from the National Longitudinal Survey of Youth 1979 data.

Responding to a 100-Year-Old Challenge from Fisher: A Biometrical Analysis of Adult Height in the NLSY Data Using Only Cousin Pairs.

In 1918, Fisher suggested that his research team had consistently found inflated cousin correlations. He also commented that because a cousin sample with minimal selection bias was not available the cause of the inflation could not be addressed, leaving this inflation as a challenge still to be solved. In the National Longitudinal Survey of Youth (the NLSY79, the NLSY97, and the NLSY-Children/Young Adult datasets), there are thousands of available cousin pairs. Those in the NLSYC/YA are obtained approximately without selection. In this paper, we address Fisher's challenge using these data. Further, we also evaluate the possibility of fitting ACE models using only cousin pairs, including full cousins, half-cousins, and quarter-cousins. To have any chance at success in such a restricted kinship domain requires an available and highly-reliable phenotype; we use adult height in our analysis. Results provide a possible answer to Fisher's challenge, and demonstrate the potential for using cousin pairs in a stand-alone analysis (as well as in combination with other biometrical designs).

Cleveland Clinic Imaging Institute's "Commitment to Respect" and Impact on Quality of Care and Patient Satisfaction.

Cleveland Clinic's Imaging Institute implemented a "Commitment to Respect" initiative and survey process in March 2013 with the goal of improving communication and teamwork among employees and, in turn, improving patient satisfaction. Since the rollout of this initiative, we have worked to increase acceptance of the process, improve the survey response, and more fully incorporate results into staff development. Now that we have 4 years of annual data for analysis, we can state based on feedback from caregivers that the process has had a positive effect on relationships between radiologists and frontline clinical staff. The survey identifies behaviors that individuals were not previously aware of, allowing staff members to make changes based on this feedback. Additionally, institute leaders are able to reinforce the respectful behaviors of those scoring well and support the efforts of those whose scores need improvement. Both scenarios are reinforced through the radiologist annual performance review process.

Double Decomposition of Level-1 Variables in Multilevel Models: An Analysis of the Flynn Effect in the NSLY Data.

This paper introduces an extension of cluster mean centering (also called group mean centering) for multilevel models, which we call "double decomposition (DD)." This centering method separates between-level variance, as in cluster mean centering, but also decomposes within-level variance of the same variable. This process retains the benefits of cluster mean centering but allows for context variables derived from lower level variables, other than the cluster mean, to be incorporated into the model. A brief simulation study is presented, demonstrating the potential advantage (or even necessity) for DD in certain circumstances. Several applications to multilevel analysis are discussed. Finally, an empirical demonstration examining the Flynn effect (Flynn, 1987 ), our motivating example, is presented. The use of DD in the analysis provides a novel method to narrow the field of plausible causal hypotheses regarding the Flynn effect, in line with suggestions by a number of researchers (Mingroni, 2014 ; Rodgers, 2015 ).

Determination of free Bisphenol A (BPA) concentrations in breast milk of U.S. women using a sensitive LC/MS/MS method.

Bisphenol A (BPA) is a synthetic, endocrine-disrupting compound. Free BPA has been detected in human samples indicating that humans are internally exposed to estrogenically active BPA. The purpose of this study was to develop a sensitive method to detect free BPA in human breast milk. BPA was isolated from the milk of 21 nursing mothers in the U.S. by solid-phase extraction. It was then derivatized to improve sensitivity and subsequently analyzed by ultra high performance liquid chromatography-tandem mass spectrometry. Free BPA was detected in 62% of the milk samples (≤ 0.22-10.8 ng mL(-1), median 0.68 ng mL(-1), mean 3.13 ng mL(-1)). No statistical difference in BPA concentrations was observed between women with a low or high Body Mass Index (BMI) (<30 (n=11) and>30 (n=10), respectively). However, there was a significant association between BPA concentration and race. Caucasian women had significantly higher levels of free BPA in their breast milk than non-Caucasian women (mean=4.44 (n=14) and 0.52 (n=7), respectively; p<0.05). The difference between races could be attributed to variations in exposure, lifestyle or metabolism and suggests that certain populations should take extra precautions to limit BPA exposure, particularly during pregnancy and lactation.

Sources of pharmaceutical pollution in the New York City Watershed.

An investigation was carried out in the New York City Watershed for the presence of selected pharmaceuticals. In four seasonal sampling events between August 2003 and May 2004, surface water was collected from eight reservoir keypoints and effluent was collected from four wastewater treatment plants. We evaluated the following twelve compounds: amoxicillin, atenolol, caffeine, carbamazepine, cephalexin, estrone, 17alpha-ethinylestradiol, 17beta-estradiol, ibuprofen, sulfamethoxazole, trimethoprim, and valproic acid. In the treated effluents, carbamazepine was detected most frequently (100%; concentration range: 22-551 ng/L), followed by atenolol (94%; ND - 14,200 ng/L), trimethoprim (83%; ND - 37,000 ng/L), ibuprofen (61%; ND - 14,600 ng/L), and caffeine (49%; ND - 37,200 ng/L), while estrone was detected once (56 ng/L). In the reservoir keypoint samples, only ibuprofen (2.5%; ND - 932 ng/L) and caffeine (2.9%; ND - 177 ng/L) were detected. The other analytes were not detected in any sample. It is expected that investigation of other wastewater treatment plants in the New York City Watershed would show that their effluents are also a potential source of pharmaceuticals, but that these pharmaceuticals are unlikely to be detected in the Watershed's surface waters.

Calcific tendonitis of the fibular collateral ligament.

This article describes calcific tendonitis within the fibular collateral ligament, presumably from hydroxyapatite deposition, a rare cause of acute, severe lateral knee pain. Imaging findings confirmed calcifications in an intact but thickened fibular collateral ligament with adjacent soft-tissue reaction, consistent with calcific tendonitis. Magnetic resonance imaging can appear aggressive, and therefore the findings often can be mistaken for other knee abnormalities; specifically, the presentation following a twisting injury that requires avulsion fracture or ligamentous injury be excluded. Confirmation of crystal deposition with thin-section CT is helpful when suspected on MRI because it is unequivocal in depicting calcifications and bony detail.

Organic pollutants in wild ducks from New York state: I. Interspecies differences in concentrations and congener profiles of PCBs and PCDDs/PCDFs.

Wild ducks of three species, common mergansers (Mergus merganser americanus), gadwalls (Anas streptera), and mallards (Anas platyrhynchos), were collected near industrial sites in the Massena, NY area of the St. Lawrence River (SLR) in 1988/89 and 1994. Additional samples were collected in 1994 near a former polychlorinated biphenyl (PCB) capacitor plant at Fort Edward, NY (a mallard and two wood ducks (Aix sponsa)), and at control sites (common mergansers, mallards and wood ducks). On a lipid basis, PCB concentrations in liver tissue from the 1994 collection ranged from 0.1 mug/g in a control wood duck to 676 mug/g in a common merganser from the SLR area. However, the highest total polychlorinated dibenzofuran (PCDF) concentrations were found in liver and fat tissues of gadwalls and mallards collected near the SLR industrial sites (2.8-12 ng/g lipid). These two species bioaccumulated non-2,3,7,8-substituted PCDFs in addition to 2,3,7,8-PCDF isomers, whereas common mergansers preferentially bioaccumulated 2,3,7,8-substituted PCDFs. The mergansers from the SLR sites were the only specimens contaminated with polychlorinated dibenzo-p-dioxins (PCDDs), which were all 2,3,7,8-substituted. The PCB and PCDF congener patterns in the duck tissues appear to have been influenced by both sampling location and species trophic level.

Unexpected diagnosis of superficial neurofibroma in a lesion with imaging features of a vascular malformation.

Plexiform neurofibroma is a pathognomonic, often disabling feature of neurofibromatosis type I. Although the target-like appearance of deep plexiform neurofibroma on T2-weighted MRI has been well-described, a second superficial form of plexiform neurofibroma has differing imaging features. We report a 15-year-old boy who presented with multiple cutaneous lesions exhibiting clinical and imaging characteristics of a venolymphatic malformation. These lesions were histologically proved to represent superficial plexiform neurofibromas. We wish to emphasize the unique MR findings of superficial plexiform neurofibromas; these findings are different from the imaging characteristics of the deep form and can be confused with a low-flow vascular malformation.